Shaping the Treatment Paradigm Based on the Current Understanding of the Pathobiology of Multiple Myeloma: An Overview
Abstract
:Simple Summary
Abstract
1. Advances on the Pathobiology of Myeloma
1.1. Genomic Aberrations in MM
1.1.1. Hyperdiploidy
1.1.2. Chromosomal Translocations
1.1.3. Copy Number Variations
1.1.4. Somatic Mutations
1.2. The Immune Tumour Microenvironment
1.2.1. T-cell Dysregulation in Myeloma
1.2.2. NK-cell Dysregulation in Myeloma
1.3. The Non-Immune Tumour Microenvironment
2. Advances on the Treatment of Multiple Myeloma
2.1. Treatment of the Newly Diagnosed MM Patient
2.1.1. Induction Therapy
TE-NDMM
TNE-NDMM
2.1.2. Consolidation and/or Maintenance
2.2. Treatment of the Relapsed/Refractory MM Patient
2.2.1. Early Relapse
2.2.2. Later Relapse
Novel Immunotherapies—ADCs, bsAbs, CAR T-cells
Small Molecules—Selinexor, Venetoclax and Iberdomide
3. Future Direction and Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Aberration Category | Genomic Aberration | Involved Oncogenes and TSG | Frequency, % | Prognosis | |
---|---|---|---|---|---|
Primary genetic events | Hyperdiploidy | Chromosomes 3, 5, 7, 9, 11, 15, 19 and 21 trisomy | Overexpression of MYC, NFκB and MAPK pathways | 50 | Favourable |
Chromosomal translocations | t(4;14) | IGH-MMSET/FGF3 | 10–15 | Adverse | |
t(11;14) | IGH-CCND1 | 15–20 | Neutral | ||
t(14;16) | IGH-MAF | 5 | Adverse | ||
t(14;20) | IGH-MAFB | 1 | Adverse | ||
Secondary genetic events | Chromosomal translocations | MYC translocations | Multiple partners incl. IGH, IGL, IGK, FAM46C, CCND1, XBP1 | 15–20 | Neutral or Adverse |
Copy number variations | 1q gain | CKS1B ANP32E BCL-9 | 35–40 | Adverse | |
1p deletion | FAM46C FAF1 CDKN2C | 30 | Adverse | ||
13q deletion * | RB1 | 45–50 | Neutral or Adverse | ||
17p deletion | TP53 | 10 | Adverse |
Clinical Study | Response Rate, % | Med PFS, Months | Overall Survival | |||||
---|---|---|---|---|---|---|---|---|
Study Population | Regimen | ORR | CR | ≥VGPR | MRDneg | |||
Newly diagnosed multiple myeloma, transplant eligible (TE) | ||||||||
IFM 2009 [78] | Phase III n = 700 Med age = 59y | VRd (x3) > VRd (x5) > R maint. vs. VRd (x3) > ASCT + VRd (x2) > R maint. | 97 vs. 98 | 48 vs. 59 p = 0.03 | 77 vs. 88 p = 0.001 | 65 vs. 79 p < 0.001 | 36 vs. 50 HR 0.65 p < 0.001 | 4yr OS 82 vs. 81% HR =1.16 p = 0.87 |
PETHEMA/GEM2012 [82] | Phase III n = 458 Med age = 58y | VRd (x6) > ASCT > VRd (x2) | 81 | 44 | 75 | 45.2 (@10−6) 65.9 (@10−4) | NR | NR |
EMN02/HO95 [79] | Phase III n = 1197 Med age = 58y | VCD induction 1st randomisation to ASCT vs. VMP intensification [results reported here] 2nd randomisation to VRd vs. observation | 95 vs. 95 | 44 vs. 40 | 84 vs. 77 | 56.7 vs. 41.9 HR = 0.73 p = 0.0001 | 5yr OS 75.1 vs. 71.6% HR = 0.90 p = 0.35 | |
ENDURANCE [83] | NDMM * No immediate intention for ASCT n = 1087 Med age = 65y * del(17p), t(14;16) & t(14;20) excluded | VRd vs. KRd Followed by second randomisation to R maintenance until PD vs. 2 yrs. | 84 vs. 87 p = 0.13 | 15 vs. 18 p = 0.261 | 65 vs. 74 p = 0.002 | 34.4 vs. 34.6 HR 1.04 p = 0.70 | 3yr OS 84 vs. 83% HR 0.98 p = 0.923 | |
FORTE [84,85] | Phase III n = 474 Med age = 57y | (A) KCd > ASCT > KCd (n = 159) (B) KRd > ASCT > KRd (n = 158) (C) KRd (x12) (n = 157) | 60 vs. 61 | 89 vs. 87 | 58 vs. 54 | Data immature | Data immature | |
Comparisons are between cohort (B) KRd > ASCT > KRd and cohort (C) KRd (x12) | ||||||||
CASSIOPEIA [84] | Phase III n = 1085 Med age = 59y | VTd vs. Dara-VTd > ASCT > VTd or Dara-VTd consolidation > 2nd randomisation to Dara maintenance vs. observation until PD | Response assessment at D100 post ASCT | |||||
89.9 vs. 92.6 p = 0.11 | 26 vs. 39 p < 0.0001 | 78 vs. 83 p = 0.024 | 20 vs. 34 p < 0.0001 | 18m PFS 85 vs. 93% HR 0.43 p < 0.0001 | Data immature | |||
GRIFFIN [69] | Phase III n = 207 Med age = 60y | VRd (x4) vs. Dara-VRd > ASCT > x2 consolidation > 2nd randomisation to R (x26) vs. Dara-R maintenance | Response assessment at end of consolidation | |||||
92 vs. 98 p = 0.016 | 32 vs. 42.4 p = 0.068 | 73 vs. 91 p = 0.0014 | 16.5 vs. 47.1 | NR at med f/u 22.1m | Data immature | |||
MASTER [85] | Phase II n = 81 Med age = 61y | Dara-KRd (x4) > ASCT > Dara-KRd (MRD-directed x4-9) > R maintenance | Response assessment at end of consolidation | |||||
100 | 95 | 100 | 82% (@10−5) | Data immature | Data immature | |||
GMMG-CONCEPT [86] | * Both TE & TNE Phase II High risk pts n = 153, interim report on n = 50 | Isa-KRd TE: Isa-KRD (x6) > ASCT; n = 46 TNE: Isa-KRd (x8); n = 4 | 100 | 46 | 90 | 31 (20/33 pts) | Data immature | Data immature |
SWOG 1211 [87] | Phase II High risk pts n = 103 Med age = 62.4y | VRd (x8) vs. Elo-VRd(x8) > attenuated VRd maintenance | 88 vs. 83 | 6 vs. 2.1 | 34 vs. 31 HR 0.97 p = 0.449 | NR vs. 68 HR 1.28 p = 0.239 | ||
Newly diagnosed multiple myeloma, transplant ineligible (TNE) | ||||||||
FIRST [88] | Phase III n = 1623 | Rd continuous vs. Rd (18 months) vs. MPT | Response assessment for Rd cohort only | |||||
81 | 22 | 48 | 26 | 59.1 | ||||
SWOG S0777 [89] | Both TE and TNE with no immediate intention for ASCT n = 460 Age ≥ 65 = 43% | Rd (x6) vs. VRd (x8) > R maintenance | 78.8 vs 90.2 | 12.1 vs. 24.2 | 53.2 vs. 74.9 | 29 vs. 41 HR 0.74 p = 0.003 | 69 vs. NR HR 0.71 p = 0.0114 | |
ALCYONE [68] | Phase III n = 706 Med age = 71y | VMP (x9) vs. Dara-VMP f/b Dara maintenance in Dara-VMP cohort | 73.9 vs. 90.9 p < 0.0001 | 25 vs. 46 p < 0.0001 | 50 vs. 73 p < 0.0001 | 7 vs. 28 p < 0.0001 | 18.1 vs. NR p < 0.001 | 36m OS estimate 67.9 vs. 78% HR 0.60 p = 0.0003 |
MAIA [67] | Phase III n = 737 Med age = 73y | Rd vs. Dara-Rd | 81.3 vs. 92.9 p < 0.001 | 24.9 vs. 47.6 p < 0.01 | 53.1 vs. 79.3 p < 0.01 | 7.3 vs. 24.2 p < 0.001 | 31.9 vs. NR HR 0.56 p < 0.001 | Data immature |
Median Progression Free Survival (mPFS), Months | |||||||||
---|---|---|---|---|---|---|---|---|---|
Study Population | Regimen | Med f/u (m) | Overall | Rnaïve | Rexp. | Rref. | PIexp. | PIref. | |
Proteasome Inhibitor-based | |||||||||
ENDEAVOR [112,113] | Phase III, n = 929 Med # PL = 2 (1–2) Prior R = 38% Prior V = 54% | Kd vs. Vd | 11.9 | 18.7 vs. 9.4 HR 0.53 p < 0.0001 | 12.9 vs. 7.3 HR 0.67 | 8.6 vs. 6.6 HR 0.80 | 15.6 vs. 8.1 HR 0.56 | ||
A.R.R.O.W. [114] | Phase III, n = 478 Med # PL = 2–3 Prior R = 84% (74.5% ref.) Prior V = 98.9% (42% ref.) | Kd 70QW vs. Kd 27BIW | 12.6 | 11.2 vs. 7.6 HR 0.69 p = 0.0029 | HR 0.72 | HR 0.76 | HR 0.73 | ||
CASTOR [115,116] | Phase III, n = 498 Med # PL = 2 (1–10) Prior IMiD = 75.7% Prior PI = 68.5% | Dara-Vd vs. Vd | 40 | 16.7 vs. 7.1 HR 0.31 p < 0.0001 | 16.7 (Dara-Vd) | 9.5 (Dara-Vd) | 7.8 (Dara-Vd) | ||
CANDOR [117] | Phase III, n = 466 Med # PL = 2 (1–2) Prior R = 42.2% (33% ref.) Prior V = 90.3% (29% ref.) | Dara-Kd vs. Kd | 17 | NR vs. 15.8 HR 0.63 p = 0.0027 | HR 0.71 | HR 0.53 | HR 0.47 | ||
IKEMA [118] | Phase III, n = 302 1–3 prior lines Prior R = 78% (33% ref.) Prior PI = 90% (33% ref.) | Isa-Kd vs. Kd | 20.7 | NR vs. 19.2 HR 0.53 p = 0.007 | |||||
Pomalidomide-based | |||||||||
Study population | Regimen | Med f/u (m) | Overall | Rnaïve | Rexp. | Rref. | PIexp. | PIref. | |
OPTIMISMM [119] | Phase III, n = 559 1–3 prior lines Prior R = 100% (70% ref.) Prior V = 72% (10% ref.) | VPd vs. Vd | 15.9 | 11.2 vs. 7.1 HR 0.61 p < 0.0001 | 11.2 | 9.5 | |||
ELOQUENT-3 [120] | Phase III, n = 117 Med # PL = 3 (range 2–8) Prior R = 99% (87% ref.) Prior V = 100% (80% ref.) | Elo-Pd vs. Pd | 9.1 | 10.3 vs. 4.7 HR 0.54 p = 0.008 | 10.2 | ||||
ICARIA [121] | Phase III, n = 307 Med # PL = 3 (range 2–4) Prior R = 100% (93% ref.) Prior V = 100% (76% ref.) | Isa-Pd vs. Pd | 11.6 | 11.5 vs. 6.5 HR 0.60 p = 0.001 | |||||
Lenalidomide-based | |||||||||
ASPIRE [122] | Phase III, n = 792 Med # PL = 2 (1–3) Prior R = 19.8% Prior V = 65.8% | KRd vs. Rd | 26.3 vs. 17.6 HR 0.69 p = 0.0001 | 28.7 (KRd) n = 317 | 19.4 (KRd) n = 79 | 9.3 (KRd) n = 57 | |||
TOURMALINE-MM1 [123] | Phase III, n= 722 1–3 prior lines Prior R = 12% Prior V =69% | Ixa-Rd vs. Rd | 14.7 | 20.6 vs. 14.7 HR 0.74 p = 0.01 | NR vs. 17.5 HR 0.74 | 18.4 vs. 13.6 HR 0.74 | |||
ELOQUENT-2 [124] | Phase Ib-II, n= 646 Med # PL = 2 (1–4) Prior R = 6% Prior V = 70% | Elo-Rd vs. Rd | 24.5 | 19.4 vs. 14.9 HR 0.70 p < 0.001 | |||||
POLLUX [125] | Phase III, n = 569 Med # PL = 1 (1–11) Prior R = 55.1% (3.7% ref.) Prior V = 86.1% (18.1% ref.) | Dara-Rd vs. Rd | 45.8 vs. 17.5 HR 0.43 p < 0.0001 | 38.6 vs. 18.6 HR 0.34 |
EVOLVE [145] | KarMMa [146] | CARTITUDE-1 [147] | |
---|---|---|---|
Product | Orvacabtagene autoleucel [orva-cel] | Idecabtagene vicleucel [ide-cel] | JNJ-4528 |
Target Antigen | BCMA | BCMA | BCMA |
n | 62 | 128 | 29 |
Median age (range) | 61 (33–77) | 61 (33–78) | 60 (50–75) |
High risk cytogenetics *, % | 41 | 35 | 27 |
Median prior lines of therapy, (range) | 6 (3–18) | 6 (3–16) | 5 (3–18) |
Triple-refractory, % | 94 | 84 | 86 |
Penta-refractory, % | 48 | 26 | 31 |
Bridging chemotherapy required, % | 63 | 88 | 79 |
Median follow-up time, months | 6.9 | 13.3 | 9.0 |
ORR, % | 92 | 73 | 100 |
sCR/CR, % | 36 | 33 | 86 |
≥VGPR, % | 68 | 53 | 97 |
MRDneg, % | 84 | 94 | 81 |
Median duration of response, months | NR | 10.7 [19.0 months in CR pts] | NR |
Median PFS, months | NR mPFS (lowest dose cohort) = 9.3 m | 8.8 (5.6–11.6) [20.2 months in CR pts] | NR 9 month PFS = 86% |
Median OS, months | NR | 19.4 (18.2-NR) | NR |
Any grade CRS, % | 89 | 84 | 93 |
≥ Grade 3 CRS, % | 3 | 6 | 7 |
Median time to CRS, days (range) | 2 (1–4) | 1 (1–12) | 7 (2–12) |
Median duration of CRS, days (range) | 4 (1–10) | 5 (1–63) | 4 (2–64) |
Any grade ICANS, % | 13 | 17 | 10 |
≥ Grade 3 ICANS, % | 3 | 3 | 3 |
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Ninkovic, S.; Quach, H. Shaping the Treatment Paradigm Based on the Current Understanding of the Pathobiology of Multiple Myeloma: An Overview. Cancers 2020, 12, 3488. https://doi.org/10.3390/cancers12113488
Ninkovic S, Quach H. Shaping the Treatment Paradigm Based on the Current Understanding of the Pathobiology of Multiple Myeloma: An Overview. Cancers. 2020; 12(11):3488. https://doi.org/10.3390/cancers12113488
Chicago/Turabian StyleNinkovic, Slavisa, and Hang Quach. 2020. "Shaping the Treatment Paradigm Based on the Current Understanding of the Pathobiology of Multiple Myeloma: An Overview" Cancers 12, no. 11: 3488. https://doi.org/10.3390/cancers12113488
APA StyleNinkovic, S., & Quach, H. (2020). Shaping the Treatment Paradigm Based on the Current Understanding of the Pathobiology of Multiple Myeloma: An Overview. Cancers, 12(11), 3488. https://doi.org/10.3390/cancers12113488